Requirements:

An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
You have 8+ years of relevant experience in software development or research work.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
A background that includes parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, etc.
Hands-on experience doing low-level performance optimizations.
In-depth expertise with CPU and GPU architecture fundamentals.
Effective communication and organization skills, with a logical approach to problem-solving, good time management, and prioritization skills.

Nice to Haves:

Expertise in parallelization and performance optimization of Deep Learning models arising from Natural Language Processing, Computer Vision, Recommender Systems, etc.
Excellent understanding of linear algebra.

In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning, or other AI domains.
Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex AI and HPC algorithms to ensure optimal AI solutions on modern CPU and GPU architectures.
Publish and/or present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the developer community.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

NVIDIA is widely considered to be one of the technology world’s most desirable employers.
Opportunity to work with forward-thinking and hardworking people in the industry.
Commitment to fostering a diverse work environment and being an equal opportunity employer.